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Abstract Thermally activated delayed fluorescence (TADF) molecules are regarded as promising materials for realizing high‐performance organic light‐emitting diodes (OLEDs). The connecting groups between donor (D) and acceptor (A) units in D–A type TADF molecules could affect the charge transfer and luminescence performance of TADF materials in aggregated states. In this work, we design and synthesize four TADF molecules using planar and twisted linkers to connect the aza‐azulene donor (D) and triazine acceptor (A). Compared with planar linkers, the twisted ones (Az‐NP‐T and Az‐NN‐T) can enhance A–A aggregation interaction between adjacent molecules to balance hole and electron density. As a result, highly efficient and stable deep‐red top‐emission OLEDs with a high electroluminescence efficiency of 57.3% and an impressive long operational lifetime (LT95 ∼ 30,000 h, initial luminance of 1000 cd m−2) are obtained. This study provides a new strategy for designing more efficient and stable electroluminescent devices through linker aggregation engineering in donor–acceptor molecules.

Oxidative stress can trigger apoptosis and associated reduction of osteoblast activity. Hinokiflavone (HNK) with a biflavonoid-based structure might show potent antioxidant activity. However, before the application of this compound as a promising therapeutic bioactive material, its interaction with blood proteins should be investigated to further reveal its pharmacokinetic and pharmacodynamic properties. Therefore, in this paper, the interaction of HNK with γ-globulin, one of the main blood proteins, was assessed. Then, the antioxidant properties of HNK against H2O2-induced osteoblast cytotoxicity in MC3T3-E1 cells were assessed. It was shown that HNK can potentially bind to γ-globulin mostly with the aid of hydrophilic forces, with a slight effect on the protein structure. It was then determined that HNK significantly recovered cell survival and alkaline phosphatase (ALP) activity and collagen-I content in MC3T3-E1 cells exposed to H2O2. In addition, HNK decreased the production of intracellular reactive oxygen species (ROS) and malondialdehyde (MDA) in MC3T3-E1 cells triggered by H2O2. Finally, HNK was shown to control the apoptosis induction in MC3T3-E1 cells triggered by H2O2 mediated by regulation of Bax, Bcl-2 and caspase-3. Taken together, these data demonstrated that HNK with promising blood protein binding properties can show significant protective effects in MC3T3-E1 cells mediated by inhibition of osteoblast dysfunction, oxidative stress, and apoptosis.

Sodium-ion batteries (SIBs) have garnered significant interest due to their potential as viable alternatives to conventional lithium-ion batteries (LIBs), particularly in environments where low-temperature (LT) performance is crucial. This paper provides a comprehensive review of current research on LT SIBs, focusing on electrode materials, electrolytes, and operational challenges specific to sub-zero conditions. Recent advancements in electrode materials, such as carbon-based materials and titanium-based materials, are discussed for their ability to enhance ion diffusion kinetics and overall battery performance at colder temperatures. The critical role of electrolyte formulation in maintaining battery efficiency and stability under extreme cold is highlighted, alongside strategies to mitigate capacity loss and cycle degradation. Future research directions underscore the need for further improvements in energy density and durability and scalable manufacturing processes to facilitate commercial adoption. Overall, LT SIBs represent a promising frontier in energy storage technology, with ongoing efforts aimed at overcoming technical barriers to enable widespread deployment in cold-climate applications and beyond.

Spherical quantum wells (SQWs) have proven to be excellent materials for suppressing Auger recombination due to their expanded confinement volume. However, research on the factors and mechanisms of their high-intensity optical properties, such as multiexciton properties and third-order optical nonlinearities, remains incomplete, limiting further optimization of these properties. Here, a series of CdS/CdSe (xML)/CdS SQWs with varying CdSe layer thicknesses were prepared. The modulation effects of CdSe shell variations on the PL properties, defect distribution, biexciton binding energy, and third-order optical nonlinearities of the SQWs were investigated, and their impact on the material’s multiexciton properties was further analyzed. Results showed that the typical CdS/CdSe(3ML)/CdS sample exhibited a large volume-normalized two-photon absorption cross-section (18.17 × 102 GM/nm3) and favorable biexciton characteristics. Optical amplification was observed at 12.4 μJ/cm2 and 1.02 mJ/cm2 under one-photon (400 nm) and two-photon (800 nm) excitation, respectively. Furthermore, different amplified spontaneous emission spectra were observed for the first time under one/two-photon excitation. This phenomenon was attributed to thermal effects overcoming the biexciton binding energy. This study provides valuable insights for further optimizing multiexciton gain characteristics in SQWs and developing optical gain applications.

Cardiac troponin I (cTnI) monitoring is of great value in the clinical diagnosis of acute myocardial infarction (AMI). In this paper, a highly sensitive electrochemical aptamer sensor using polystyrene (PS) microspheres as the electrode substrate material in combination with Prussian blue (PB) and gold nanoparticles (AuNPs) was demonstrated for the sensitive and label-free determination of cTnI. PS microspheres were synthesized by emulsion polymerization and then dropped onto the glassy carbon electrode (GCE); PB and AuNPs were electrodeposited on the electrode in corresponding electrolyte solutions step by step. The PS microsphere substrate provided a large surface area for the loading mass of the biological affinity aptamers, while the PB layer improved the electrical conductivity of the modified electrode, and the electroactive AuNPs exhibited excellent catalytic performance for the subsequent electrochemical measurements. In view of the above mentioned AuNPs/PB/PS/GCE sensing platform, the fabricated label-free electrochemical aptamer sensor exhibited a wide detection range of 10 fg/mL~1.0 μg/mL and a low detection limit of 2.03 fg/mL under the optimal conditions. Furthermore, this biosensor provided an effective detection platform for the analysis of cTnI in serum samples. The introduction of this sensitive electrochemical aptamer sensor provides a reference for clinically sensitive detection of cTnI.

The development and application of virtual reality (VR) technology significantly enhances consumer immersion. Exploring a multi-sensory evaluation model for virtual packaging is valuable for integrating VR technology with packaging. This study developed a multi-sensory evaluation model for virtual packaging using the analytic hierarchy process (AHP). Eye-tracker experimentation was conducted to identify consumer attention indicators when interacting with virtual packaging. These indicators were quantified using Saaty’s nine-level importance scale and expert input, resulting in a comprehensive multi-sensory evaluation model. Subsequently, a VR shopping system focused on potato chips and cola as packaging design objects. This system was evaluated using the established model, and the results were analyzed. Based on the findings, improvements were made, and the system was re-evaluated using the modified model. The post-improvement evaluation demonstrated significantly enhanced sensory experiences. These results validate that the developed evaluation model effectively guides multi-sensory design approaches for packaging within a VR environment.

Abstract The low mechanical strength, water deficiency, and oxidative protection of organic membranes impede their use as food-grade packaging materials. Cinnamaldehyde (CIN) tends to lose its activity owing to its instability. In this study, CIN was added to flaxseed gum (FG)/chitosan (CS) films prepared in a “sandwich” structure. The influence of CIN dosage on the properties of the composite films was studied, and the film formation mechanism of the membrane was explored. The elongation at break, water vapor permeability, oxygen permeability, and light transmittance of the composite film with 1.5% CIN were lower than those of the FG/CS/FG film. Supplementation of the composite membrane with CIN generated new hydrogen bonds, electrostatic interactions, and C-O-C bonds, which converted the structure of the composite film into a sheet and increased its crystallinity without markedly affecting its thermal stability. Therefore, CIN is an extremely useful additive for improving the applicability of flaxseed gum/CS membranes as food-grade packaging films.

Intelligent and diversified development of modern detection technology greatly affects the battlefield survivability of military targets, especially infrared, acoustic wave, and radar detection expose targets by capturing their unavoidable infrared radiation, acoustic wave, and electromagnetic wave information, greatly affecting their battlefield survival and penetration capabilities. Therefore, there is an urgent need to develop stealth-protective materials that can suppress infrared radiation, reduce acoustic characteristics, and weaken electromagnetic signals. Fibrous three-dimensional porous materials, with their high porosity, excellent structural adjustability, and superior mechanical properties, possess strong potential for development in the field of stealth protection. This article introduced and reviewed the characteristics and development process of fibrous three-dimensional porous materials at both the micrometer and nanometer scales. Then, the process and characteristics of preparing fibrous three-dimensional porous materials through vacuum forming, gel solidification, freeze-casting, and impregnation stacking methods were analyzed and discussed. Meanwhile, their current application status in infrared, acoustic wave, and radar stealth fields was summarized and their existing problems and development trends in these areas from the perspectives of preparation processes and applicability were analyzed. Finally, several prospects for the current challenges faced by fibrous three-dimensional porous materials were proposed as follows: functionally modifying fibers to enhance their applicability through self-cross-linking; establishing theoretical models for the transmission of thermal energy, acoustic waves, and electromagnetic waves within fibrous porous materials; constructing fibrous porous materials resistant to impact, shear, and fracture to meet the needs of practical applications; developing multifunctional stealth fibrous porous materials to confer full-spectrum broadband stealth capability; and exploring the relationship between material size and mechanical properties as a basis for preparing large-scale samples that meet the application’s requirement. This review is very timely and aims to focus researchers’ attention on the importance and research progress of fibrous porous materials in the field of stealth protection, so as to solve the problems and challenges of fibrous porous materials in the field of stealth protection and to promote the further innovation of fibrous porous materials in terms of structure and function.

Shale is composed of a rock matrix and bedding planes with a layered structure, resulting in significant anisotropy in its mechanical properties. In order to study the anisotropic mechanical properties of shale, the shale samples were prepared in different orientations with respect to the bedding planes, and the composition and microstructure of shale were first analyzed by X-ray diffractometer (XRD) and scanning electron microscope (SEM), and then the uniaxial and triaxial compression experiment on shale samples with five different bedding angles (the angle between the loading direction and the normal direction of the bedding planes, 0°, 30°, 45°, 60°, and 90°) were conducted under five confining pressures (0, 10, 20, 30, and 40 MPa), respectively; meanwhile, the acoustic emission (AE) test was carried out in the uniaxial test. The results indicate that the mechanical properties and parameters of shale have obvious anisotropy, and the AE characteristics of shale samples with different bedding angles are significantly different during uniaxial loading. Furthermore, the compressive strength and elastic modulus of the shale samples first decrease and then increase with the increase in the bedding angle under different confining pressures. Moreover, according to the anisotropic grade of compressive strength, the shale has moderate anisotropy. In addition, the failure mode of the shale samples is also anisotropic, and varies with the bedding angle and confining pressure.

In recent years, the continuous progress of wireless communication and sensor technology has enabled sensors to be better integrated into mobile devices. Therefore, sensor-based Human Activity Recognition (HAR) has attracted widespread attention among researchers, especially in the fields of wearable technology and ubiquitous computing. In these applications, mobile devices’ built-in accelerometers and gyroscopes have been typically used for human activity recognition. However, devices such as smartphones were placed in users’ pockets and not fixed to their bodies, and the resulting changes in the orientation of the sensors due to users’ habits or external forces can lead to a decrease in the accuracy of activity recognition. Unfortunately, there is currently a lack of publicly available datasets specifically designed to address the issue of device angle change. The contributions of this study are as follows. First, we constructed a dataset with eight different sensor placement angles using accelerometers and gyroscopes as a prerequisite for the subsequent research. Second, we introduced the Madgwick algorithm to extract quaternion mode features and alleviate the impact of angle changes on recognition performance by fusing raw accelerometer data and quaternion mode features. The resulting study provides a comprehensive analysis. On the one hand, we fine-tuned ResNet and tested its stability on our dataset, achieving a recognition accuracy of 97.13%. We included two independent experiments, one for user-related scenarios and the other for user-independent scenarios. In addition, we validated our research results on two publicly available datasets, demonstrating that our method has good generalization performance.

Low-quality cotton fibers, often overlooked as low-value materials, constitute a marginalized waste stream in the cotton industry. This study endeavored to repurpose these fibers into mulch gel films, specifically exploring their efficacy in covering moisture-controlled soil beds. Through a meticulously designed series of processing methods, cellulose/glycerol film was successfully fabricated by regenerating cellulose hydrogels in N,N-dimethylacetamide/lithium chloride solutions, followed by plasticization in glycerol/water solutions and hot pressing. The film was then employed to cover soil beds for a duration of up to 252 days, followed by soil burial assessments. Despite expectations of degradation, the film maintained structural integrity throughout the soil covering period but underwent complete biodegradation after 80 days of soil burial, thereby completing a closed carbon cycle. Intriguingly, both tensile strength and modulus exhibited no diminishment but instead increased after soil covering, contrary to expectations given the usual role of degradation. Mechanistic insights revealed that the removal of glycerol contributed to the mechanical enhancement, while microbial activity predominately decomposed the amorphous regions in soil covering and targeted the crystalline portions in soil burial, elucidating the main biodegradation mechanisms. In summary, this study presents, for the first time, the potential of upcycling low-quality cotton fibers into high-value mulch gel films for agricultural practices within a closed carbon cycle.

To investigate the susceptibility of drifting snow along the Ya’an–Qamdo section of the railway, which is located in a high-altitude and cold plateau in Southwest China with scarce meteorological information, the Weather Research and Forecasting Model (WRF) is used in this paper to simulate the spatio-temporal distribution of meteorological data. According to the varying terrain, the railway section from Ya’an to Qamdo is divided into two regions along 100.8° E for double-layer nested simulation. The original land use data of the WRF model are used in region 1. Due to the increased number of mountains in region 2, the original data are replaced by the MCD12Q1v006 land use data, and the vertical direction layers are densified near the ground to increase simulation accuracy. The simulated results are compared with the observation data. It is found that after densification, the results have been significantly improved. The results obtained by the WRF model can accurately simulate the change trends of temperature, rainfall, and wind speed, and the correlation coefficients are relatively high, which verifies the accuracy of WRF for simulating complex terrain regions. The simulation results further indicate that approximately 300 km of the Ya’an–Qamdo railway may experience drifting snow. Among them, no drifting snow events occur in Ya’an County, and the areas with higher probability are located at the border between Luding County and Tianquan County, followed by Kangding area. The remaining areas have a probability of less than 10%. The WRF model demonstrates its capability in the drifting snow protection of railways with limited meteorological data.

In the field of deep-sea positioning, this paper aims to enhance accuracy and computational efficiency in positioning calculations. We propose an improved method based on layered clustering of sound velocity profiles, where the profiles are stratified according to maximum distance and maximum density. Subsequently, a secondary curve fitting is applied to the stratified data. Ultimately, the underwater positioning is conducted using the sound velocity profiles’ post-layered fitting. We compare our approach with traditional methods such as k-means clustering, layered clustering, and gradient-based stratification. Experimental results demonstrate that, in the application scenario of a USBL system with a transducer tilted at 30°, and under the premise of autonomously controlling the number of layers, our method significantly improves positioning accuracy.

In order to effectively estimate the depth of the source in the acoustic pressure field, this study investigated the relationship between the distribution of acoustic pressure fields in different adjacent mode groups and the depth of the source in shallow waveguides and proposed a method to estimate the depth of the source on the basis of the adjacent mode group acoustic pressure field. We first derived and calculated the adjacent mode group acoustic pressure field of a typical shallow waveguide, then verified the accuracy of this derivation process through simulations. In addition, combined with singular value decomposition mode extraction, the adjacent mode group acoustic pressure field of the SACLANT experimental data was obtained and used as a comparative parameter for the method presented in this paper. By using the depth of the source as the estimation variable, a simulated annealing algorithm and related parameters were designed, and the feasibility of this method was verified through simulation and experiments. The proposed method achieved a higher localization accuracy without the need for accurate modeling of underwater acoustic channels. Under the conditions of the simulation environment, the average estimation error rate of the method was 0.24%, and with increases in the temperature coefficient and Markov chain length, the average estimation error rate of the method decreased. In the experimental environment, the average estimation error rate of the method was 0.45%. This study provides a method to obtain the depth of source in a shallow waveguide via the adjacent mode group acoustic pressure field.

The environmental impact of industrial development has been well-documented. The use of physical and chemical methods in industrial development has negative consequences for the environment, raising concerns about the sustainability of this approach. There is a growing need for advanced technologies that are compatible with preserving the environment. The use of fungi products for nanoparticle (NP) synthesis is a promising approach that has the potential to meet this need. The genus Trichoderma is a non-pathogenic filamentous fungus with a high degree of genetic diversity. Different strains of this genus have a variety of important environmental, agricultural, and industrial applications. Species of Trichoderma can be used to synthesize metallic NPs using a biological method that is environmentally friendly, low cost, energy saving, and non-toxic. In this review, we provide an overview of the role of Trichoderma metabolism in the synthesis of metallic NPs. We discuss the different metabolic pathways involved in NP synthesis, as well as the role of metabolic metabolites in stabilizing NPs and promoting their synergistic effects. In addition, the future perspective of NPs synthesized by extracts of Trichoderma is discussed, as well as their potential applications in biomedicine, agriculture, and environmental health.

Introduction: Fusidic acid (FA) has been widely applied in the clinical prevention and treatment of bacterial infections. Nonetheless, its clinical application has been limited due to its narrow antimicrobial spectrum and some side effects.Purpose: Therefore, it is necessary to explore the structure–activity relationships of FA derivatives as antibacterial agents to develop novel ones possessing a broad antimicrobial spectrum.Methods and result: First, a pharmacophore model was established on the nineteen FA derivatives with remarkable antibacterial activities reported in previous studies. The common structural characteristics of the pharmacophore emerging from the FA derivatives were determined as those of six hydrophobic centers, two atom centers of the hydrogen bond acceptor, and a negative electron center around the C-21 field. Then, seven FA derivatives have been designed according to the reported structure–activity relationships and the pharmacophore characteristics. The designed FA derivatives were mapped on the pharmacophore model, and the Qfit values of all FA derivatives were over 50 and FA-8 possessed the highest value of 82.66. The molecular docking studies of the partial target compounds were conducted with the elongation factor G (EF-G) of S. aureus. Furthermore, the designed FA derivatives have been prepared and their antibacterial activities were evaluated by the inhibition zone test and the minimum inhibitory concentration (MIC) test. The derivative FA-7 with a chlorine group as the substituent group at C-25 of FA displayed the best antibacterial property with an MIC of 3.125 µM. Subsequently, 3D-QSAR was carried on all the derivatives by using the CoMSIA mode of SYBYL-X 2.0.Conclusion: Hence, a computer-aided drug design model was developed for FA, which can be further used to optimize FA derivatives as highly potent antibacterial agents.

High-voltage direct current (HVDC) blocking disturbance leads to large power losses in the receiving-end power grid, and the event-driven emergency frequency control (EFC) is an important measure to prevent large frequency deviation. By aggregating controllable distributed energy resources (DERs) on the demand side, a virtual power plant (VPP) could quickly reduce its power and can be a new fast response resource for EFC. Considering both the VPP and the traditional control resources, this paper proposes an optimized EFC strategy coordinating multiple resources for the receiving-end power grid with multi-infeed HVDC. The approximate aggregation model of the VPP response process is constructed, based on which the EFC strategy, aiming at minimizing the total control cost while meeting constraints on rotor angle stability and frequency deviation security, is proposed. The electromechanical transient simulation combined with particle swarm optimization (PSO) is utilized to solve the model, and parallel computation is utilized to accelerate the solving process. The effectiveness of the proposed EFC strategy is verified by a provincial receiving-end power grid with multi-infeed HVDC. The detailed simulation results show that VPP could dramatically reduce the control cost of EFC while maintaining the same stability margin.

As the use of digital currencies, such as cryptocurrencies, increases in popularity, phishing scams and other cybercriminal activities on blockchain platforms (e.g., Ethereum) have also risen. Current methods of detecting phishing in Ethereum focus mainly on the transaction features and local network structure. However, these methods fail to account for the complexity of interactions between edges and the handling of large graphs. Additionally, these methods face significant issues due to the limited number of positive labels available. Given this, we propose a scheme that we refer to as the Bagging Multiedge Graph Convolutional Network to detect phishing scams on Ethereum. First, we extract the features from transactions and transform the complex Ethereum transaction network into three simple inter-node graphs. Then, we use graph convolution to generate node embeddings that leverage the global structural information of the inter-node graphs. Further, we apply the bagging strategy to overcome the issues of data imbalance and the Positive Unlabeled (PU) problem in transaction data. Finally, to evaluate our approach’s effectiveness, we conduct experiments using actual transaction data. The results demonstrate that our Bagging Multiedge Graph Convolutional Network (0.877 AUC) outperforms all of the baseline classification methods in detecting phishing scams on Ethereum.

With the accelerating penetration of photovoltaics (PVs) and electric vehicles (EVs), distribution networks face the risks of voltage violations and fluctuations. On the one hand, conventional voltage regulation resources like OLTC transformers and capacitor banks feature slow response and limited lifetime duration, making them incapable of quickly responding to the temporary voltage issues created by PVs and EVs. On the other hand, EVs and PVs interact with the power grid via fully controllable power electronic converters capable of real-time adjusting their operating settings, making them ideal voltage support resources. To exploit the voltage support capability of PVs and EVs, this paper proposes a two-stage control scheme for the voltage regulation of distribution networks, consisting of the day-ahead and intraday control stages. The day-ahead control mitigates potential voltage violations via day-ahead scheduling of the operation settings for OLTC transformers and capacitor banks. The intraday control further alleviates voltage deviations and voltage fluctuations based on the reactive power support of PV systems and the rational EV charging/discharging scheduling. A rolling optimization-based control technique is proposed in the intraday control stage to achieve real-time control of EVs and PVs with the stochastic nature of EV charging behaviors inherently considered. The proposed two-stage voltage regulation scheme is validated via case studies performed on the IEEE 123-node test feeder integrated with PVs and EVs.

The detection of moving objects in images is a crucial research objective; however, several challenges, such as low accuracy, background fixing or moving, ‘ghost’ issues, and warping, exist in its execution. The majority of approaches operate with a fixed camera. This study proposes a robust feature threshold moving object identification and segmentation method with enhanced optical flow estimation to overcome these challenges. Unlike most optical flow Otsu segmentation for fixed cameras, a background feature threshold segmentation technique based on a combination of the Horn–Schunck (HS) and Lucas–Kanade (LK) optical flow methods is presented in this paper. This approach aims to obtain the segmentation of moving objects. First, the HS and LK optical flows with the image pyramid are integrated to establish the high-precision and anti-interference optical flow estimation equation. Next, the Delaunay triangulation is used to solve the motion occlusion problem. Finally, the proposed robust feature threshold segmentation method is applied to the optical flow field to attract the moving object, which is the. extracted from the Harris feature and the image background affine transformation model. The technique uses morphological image processing to create the final moving target foreground area. Experimental results verified that this method successfully detected and segmented objects with high accuracy when the camera was either fixed or moving.

The Industrial Internet of Things (IIoT) accelerates smart manufacturing and boosts production efficiency through heterogeneous industrial equipment, intelligent sensors, and actuators. The Industrial Internet of Things is transforming from a traditional factory model to a new manufacturing mode, which allows cross-domain data-sharing among multiple system departments to enable smart manufacturing. A complete industrial product comes from the combined efforts of many different departments. Therefore, secure and reliable cross-domain access control has become the key to ensuring the security of cross-domain communication and resource-sharing. Traditional centralized access control schemes are prone to single-point failure problems. Recently, many researchers have integrated blockchain technology into access control models. However, most blockchain-based approaches use a single-chain structure, which has weak data management capability and scalability, while ensuring system security, and low access control efficiency, making it difficult to meet the needs of multi-domain cooperation in IIoT scenarios. Therefore, this paper proposes a decentralized cross-domain access model based on a master–slave chain with high scalability. Moreover, the model ensures the security and reliability of the master chain through a reputation-based node selection mechanism. Access control efficiency is improved by a grouping strategy retrieval method in the access control process. The experimental benchmarks of the proposed scheme use various performance metrics to highlight its applicability in the IIoT environment. The results show an 82% improvement in the throughput for the master–slave chain structure over the single-chain structure. There is also an improvement in the throughput and latency compared to the results of other studies.

In this study, flaxseed gum (FG) was extracted using hot water extraction and ultrasonic-assisted extraction. The yield, molecular weight distribution, monosaccharide composition, structure, and rheological properties of FG were analyzed. The FG yield (9.18) achieved using ultrasound-assisted extraction (this sample was labeled as UAE) was higher than the yield (7.16) achieved with hot water extraction (this sample was labeled as HWE). The polydispersity, monosaccharide composition, and characteristic absorption peaks of the UAE were similar to that of the HWE. However, the UAE had a lower molecular weight and looser structure than the HWE. Moreover, zeta potential measurements indicated that the UAE exhibited better stability. An analysis of the rheological properties showed that the viscosity of the UAE was lower. Thus, the UAE had an effectively better yield of FG, preliminarily modified structure, and rheological properties, and provided a theoretical basis for its application in food processing.

The stability of high backfill slopes emerges in practice due to the expansion of transportation infrastructures. The seepage and infiltration of rainfall into the backfills brings challenges to engineers in predicting the stability of the slope, weakening the shear strength and modulus of the soil. This study carried out a series of model tests under a plane strain condition to investigate the stability of a high backfill slope moisturized by rainfalls, considering the influences of rainfall duration and intensity. The slope displacements were monitored by a laser displacement sensor and the moisture content in the backfill mass were obtained by a soil moisture sensor. The test results show that increasing the rainfall intensity and duration caused the slope near the surface to be saturated, resulting in significant influences on the lateral displacement of the slope and the reduction of stability as well as the sizes of the sliding mass. Based on the model tests, the numerical analysis was adopted to extend the analysis cases, and the backpropagation (BP) neural network model was further adopted to build a model for predicting the stability of a high backfill slope under rainfall. The trained BP model shows the average relative error of 1.02% and the goodness of fitness of 0.999, indicating a good prediction effect.

Structural unsteadiness and sluggish diffusion of divalent zinc cations in cathodes during cycling severely limit further applications of MoS2 for rechargeable aqueous zinc-ion batteries (ZIBs). To circumvent these hurdles, herein, phosphorus (P) atom embedded three-dimensional marigold-shaped 1T MoS2 structures combined with the design of S vacancies (Sv) are synthesized via the oxygen-assisted solvent heat method. The oxygen-assisted method is utilized to aid the P-embedding into the MoS2 crystal, which can expand the interlayer spacing of P-MoS2 and strengthen Zn2+ intercalation/deintercalation. Meanwhile, the three-dimensional marigold-shaped structure with 1T phase retains the internal free space, can adapt to the volume change during charge and discharge, and improve the overall conductivity. Moreover, Sv is not only conducive to the formation of rich active sites to diffuse electrons and Zn2+ but also improves the storage capacity of Zn2+. The electrochemical results show that P-MoS2 can reach a high specific capacity of 249 mAh g−1 at 0.1 A g−1. The capacity remains at 102 mAh g−1 after 3260 cycles at a current of 0.5 A g−1, showing excellent electrochemical performance for Zn2+ ion storage. This research provides a more efficient method of P atom embedded MoS2-based electrodes and will heighten our comprehension of developing cathodes for the ZIBs.

Magneto-optical materials are the fundamental component of Faraday isolators; therefore, they are significantly important for solid-state laser systems. Fluoride magneto-optical crystals such as CeF3, KTb3F10 and LiTbF4 exhibit advantages of wide transmittance range, high optical homogeneity, smaller thermal lensing and weaker thermal induced depolarization effect, and thus are promising candidates for Faraday isolators in high-power solid-state lasers. Recent progress in crystal growth and characterizations of these fluoride magneto-optical crystals are introduced. Possible applications of Faraday isolators based on various fluoride crystals are discussed, especially for solid-state lasers in the ultraviolet (UV) or infrared (IR) spectral region.

The detection of bolt loosening using vibro-acoustic modulation (VAM) has been increasingly investigated in the past decade. However, conventional nonlinear coefficients, derived from theoretical analysis, are usually based on the assumption of ideal wave–surface interactions at the joint interfaces. Such coefficients show a poor correlation with the tightening torque when the joint is under the combined influences of structural and material nonlinearities. A reliable inspection method of residual bolt torque is proposed in this study using support vector regression (SVR) with acoustic features from VAM. By considering the material intrinsic nonlinearity (MIN) and dissipative nonlinearity (DN), the responses of aluminum–aluminum and composite–composite bolted joints during the VAM test were accurately simulated. The SVRs were subsequently established based on the database built by combining simulated and experimental nonlinear spectral features when the joints were inspected at different scenarios. The results show that the evaluation of residual torque using the SVR models driven by the acoustic nonlinear responses had higher accuracy compared to the conventional nonlinear coefficients. Requiring limited experimental data, the proposed method can achieve a reliable inspection of bolt torque by including the simulated data in the machine training.

Maximum power point tracking (MPPT) is the key to improve the conversion efficiency of wind energy. Concerning the current research on the MPPT control, based on the accurate tracking of rotor speed probability density function (PDF) shape for wind turbines, a novel MPPT algorithm was introduced in detail to improve the power capture and reduce mechanical damage for wind turbines. Considering the influence of wind speed distribution on the wind power generation system performance, this paper expounds a PDF shape control method of a stochastic system based on the Fokker–Planck–Kolmogorov (FPK) equation. Combining the conventional optimal torque (OT) control algorithm with the FPK equation solved by linear least-square (LLS) method, the novel MPPT control law is designed to make the PDF shape of rotor speed track the desired PDF shape as accurately as possible. The simulation verification of the novel MPPT method is carried out in the 1.5 MW wind turbine system. The results reveal that the novel MPPT method can improve the conversion efficiency of wind energy, reduce the frequent fluctuations of system variables, and significantly optimize the performance of wind power generation system.

TiO2 has limited applicability as an alternative to noble metal electrocatalysts for the hydrogen evolution reaction in aqueous solution due to the possibility of hydrogen intercalation under cathodic potential. In this work, the electrolytic reduction of H2O on TiO2 electrodes in alkaline media is investigated. Cyclic voltammetry experiments, combined with X-ray diffraction and in situ UV–vis results, indicate that most of the H species produced during the reaction diffuse into the TiO2 bulk at high cathodic potential. However, the presence of Au particles on the TiO2 electrodes greatly enhances H2O reduction and H2 production due to the H spillover effects, i.e., the H species produced on the TiO2 spill over to the Au nanoparticles and recombine to form H2. This result provides a new way of thinking about the design of more effective catalysts for the hydrogen evolution reaction using transition metal oxides.

In order to improve the mixture ratio accuracy of the bipropellant thruster and prolong the service life of a satellite on orbit, a variety of different liquid-flow tests and the final firing test are critical in the production testing process. However, after comparison with a large number of tests data, it was found that the liquid-flow test results were far away from matching the firing-test data without clear regularity, resulting in a qualified rate of mixture ratio of less than 40%. This study developed a BP-RNN (back propagation—recurrent neural network) chain method based on machine learning, which uses multi-dimensional nonlinear parameters to construct the specific dataset after data enhancement. Then, the mapping characteristic of the neural network was used to fit the historical data for the weight analysis and mixture ratio prediction, and effectively improved the qualified rate of the mixture ratio. The back propagation neural network was used to learn the association rules of the 10-dimension characteristic data and the firing test results generated in the historical process of thruster production. Then, the features with high influencing weight were extracted and sorted, so the “many-to-one” mixture ratio prediction was conducted through the subsequent recurrent neural network. The accepted prediction accuracy could reach around 75% after the test data verification. By using this method, most of bipropellant thrusters could directly reach the qualified mixture ratio in the firing test after adjusting the throttle orifice size in the liquid-flow tests. This chain method first bridges the data between the liquid-flow test and the firing test.

Adding organic compounds to wastewater can improve the carbon/nitrogen ratio and benefit microalgae growth. We studied microalgal growth, nutrient removal and lipid accumulation of Chlorella pyrenoidosa cultured in a mixture of swine wastewater (SW) and furfural wastewater (FW). The mix ratio of SW:DFW (diluted furfural wastewater) had a significant effect on microalgae growth. As the mix ratio of SW:DFW decreased from 1:0.5 to 1:19, the maximum microalgal biomass increased, while the specific growth rate initially increased and then decreased. The efficiency of nutrient removal also depended on the mix ratio of wastewater. The highest chemical oxygen demand (COD) removal efficiency (57.30%) occurred at the mix ratio of SW:DFW = 1:3. The highest removal efficiencies of total phosphorous (TP) reached 61.93% when the mix ratio of SW:DFW was 1:9. Wastewater at the mix ratio of SW:DFW = 1:19 had a maximum lipid productivity of 49.48 mg L−1 d−1, which was 4.9 times higher than that at a mix ratio of SW:DFW = 1:0.5. These results showed that C. pyrenoidosa can be used to remove nutrients from mixed wastewater sources and simultaneously produce algal lipids.

The surface coating properties of turbine blades are highly dependent on the material’s surface roughness, and the femtosecond laser-induced micro-structure can provide a wide range of roughness with periodicity. However, precise control of femtosecond laser-induced micro-structure is difficult. In this paper, we extend the application of the two-temperature model and combine it with experiments to accurately reveal the evolution law of micro-structure depth at different single pulse energies, as well as the influence of two processing parameters on micro-structure, namely, defocusing amount and scanning speed. The findings of this study provide reliable theoretical guidance for fast and accurate control of material surface roughness and open new possibilities for coating properties.

Transformer-based neural machine translation (NMT) has achieved state-of-the-art performance in the NMT paradigm. This method assumes that the model can automatically learn linguistic knowledge (e.g., grammar and syntax) from the parallel corpus via an attention network. However, the attention network cannot capture the deep internal structure of a sentence. Therefore, it is natural to introduce some prior knowledge to guide the model. In this paper, factual relation information is introduced into NMT as prior knowledge, and a novel approach named Factual Relation Augmented (FRA) is proposed to guide the decoder in Transformer-based NMT. In the encoding procedure, a factual relation mask matrix is constructed to generate the factual relation representation for the source sentence, while in the decoding procedure an effective method is proposed to incorporate the factual relation representation and the original representation of the source sentence into the decoder. Positive results obtained in several different translation tasks indicate the effectiveness of the proposed approach.

Hydrogels play important roles in function materials, especially in wastewater treatment, that could solve the problems of microbial infections and dye pollutions. Herein, a natural glycyrrhetinic acid-derived gel was successfully constructed by forming hierarchical assemblies of the glycyrrhetinic acid derivatives (GA-O-09) with Cu2+. Interestingly, the GA-O-09/Cu2+ gel exhibited Cu2+-triggered shrinkage, which was helpful for spontaneous self-demolding through the shrinkage process with a precise amount of Cu2+. Moreover, the gel showed excellent antimicrobial activity against Staphylococcus aureus and methicillin-resistant Staphylococcus aureus (MRSA) with minimum inhibitory concentrations (MICs) at 2.5 μg/mL and 5.0 μg/mL, respectively. Furthermore, the resultant GA-O-09/Cu2+ gel showed an excellent performance in dyes removal; the adsorption capacity at equilibrium (qe) could reach 82.91 mg/g according to a pseudo-second-order model, and it was better than most reported dye adsorbent materials. The experimental result suggested that the electrostatic interactions of the hydrogel with the cationic dyes and the hydrogel swelling were responsible for the possible dye removal mechanism of GA-O-09/Cu2+ gel. Therefore, our study holds the promise of a better future, for such a hydrogel could be used as an antibacterial and dye removal material.

Annular pressure has been recognized as one of the most challenging problems in the petroleum industry, posing a series of threats to wellbore integrity. Annular pressure caused by thermal expansion during the cement hydration process is rarely studied by researchers. In light of the hydration heat generation process, a kinetics model for cement hydration under different curing temperatures is demonstrated in this paper. Considering interactions between temperature and cement hydration, a transient temperature prediction model during well cementing is built. On the basis of these assumptions, the prediction model of annular pressure is established, considering the change in cement temperature and the change in annulus volume. Using the models illustrated in this paper, a series of numerical simulations are performed. The changing roles of transient cement hydration degree and temperature in wellbores are analyzed thoroughly. The annular pressure during well cementing shows a rapid increase and then a decrease, which is similar to that of the temperature. In addition, a sensitive analysis of annular pressure is conducted. The analysis shows that the annular pressure increases with the geothermal gradient, the cement hydration heat, and the wellbore diameter. Suggestions and conclusions can provide safety guidance for the management of annular pressure during well cementing.

Six luminophores bearing an OBO-fused benzo[fg]tetracene core as an electron acceptor were designed and synthesized. The molecular structures of three molecules (PXZ-OBO, 5PXZ-OBO, 5DMAC-OBO) were determined by single crystal X-ray diffraction studies and revealed significant torsion between the donor moieties and the OBO acceptor with dihedral angles between 75.5 and 86.2°. Photophysical studies demonstrate that blue and deep blue emission can be realized with photoluminescence maxima (λPL) ranging from 415 to 480 nm in mCP films. The emission energy is modulated by simply varying the strength of the donor heterocycle, the number of donors, and their position relative to the acceptor. Although the DMAC derivatives show negligible delayed emission because of their large singlet-triplet excited state energy difference, ΔEST, PXZ-based molecules, especially PXZ-OBO with an experimental ΔEST of 0.25 eV, demonstrate delayed emission in blend mCP films at room temperature, which suggests triplet exciton harvesting occurs in these samples, potentially by thermally activated delayed fluorescence.

Thermally-activated delayed fluorescence (TADF) emitters—just like phosphorescent ones—can in principle allow for 100% internal quantum efficiency of organic light-emitting diodes (OLEDs), because the initially formed electron-hole pairs in the non-emissive triplet state can be efficiently converted into emissive singlets by reverse intersystem crossing. However, as compared to phosphorescent emitter complexes with their bulky—often close to spherical—molecular structures, TADF emitters offer the advantage to align them such that their optical transition dipole moments (TDMs) lie preferentially in the film plane. In this report, we address the question which factors control the orientation of TADF emitters. Specifically, we discuss how guest-host interactions may be used to influence this parameter and propose an interplay of different factors being responsible. We infer that emitter orientation is mainly governed by the molecular shape of the TADF molecule itself and by the physical properties of the host—foremost, its glass transition temperature Tg and its tendency for alignment being expressed, e.g., as birefringence or the formation of a giant surface potential of the host. Electrostatic dipole-dipole interactions between host and emitter are not found to play an important role.

We demonstrated a passively Q-switched Er:Ca0.8Sr0.2F2 laser with indium tin oxide nanowire arrays as an optical modulator in the mid-infrared region. In the Q-switched regime, the maximum output power of 58 mW with a slope efficiency of 18.3% was acquired. Meanwhile, the minimum pulse duration and highest repetition rate of the stable pulse trains were 490 ns and 17.09 kHz, corresponding to single pulse energy of 3.4 μJ and peak power of 6.93 W, respectively. To the best of our knowledge it was the first time that indium tin oxide nanowire arrays were employed as a saturable absorber to make pulse lasers carried out at 2.8 μm. The experimental data show that indium tin oxide nanowire arrays can be employed as a competitive candidate for saturable absorber in the field of mid-infrared solid-state lasers.

Automatic segmentation and centerline extraction of blood vessels from retinal fundus images is an essential step to measure the state of retinal blood vessels and achieve the goal of auxiliary diagnosis. Combining the information of blood vessel segments and centerline can help improve the continuity of results and performance. However, previous studies have usually treated these two tasks as separate research topics. Therefore, we propose a novel multitask learning network (MSC-Net) for retinal vessel segmentation and centerline extraction. The network uses a multibranch design to combine information between two tasks. Channel and atrous spatial fusion block (CAS-FB) is designed to fuse and correct the features of different branches and different scales. The clDice loss function is also used to constrain the topological continuity of blood vessel segments and centerline. Experimental results on different fundus blood vessel datasets (DRIVE, STARE, and CHASE) show that our method can obtain better segmentation and centerline extraction results at different scales and has better topological continuity than state-of-the-art methods.

To study the static and dynamic response of micropile-reinforced slopes, static model tests and shaking table tests were performed. The failure modes, the pile-slope interaction, the displacement, and the static/dynamic earth pressure distributions were analyzed based on static and dynamic model tests with a prescribed sliding surface. The test results indicated: (1) The micropile failure mode is mainly bending failure under both loading conditions. As far as the damage to the pile body is concerned, under static loading, the rear row piles showed more damage than the middle row piles followed by the front row piles. Under dynamic loading, the damage of the rear row piles was approximately the same as the middle row piles, which was greater than the front row piles; (2) The earth pressures in front of and behind each row of micropiles and the axial force of the pile body distributed triangularly for both loading conditions, with the bending moment of the pile body distributed in an “S” shape; (3) The landslide thrust experienced by the micropiles has a relatively large group effect. The group effect or shear ratio parameters are recommended for each loading case; (4) The interaction between the micropiles and the soil landslide presents evident progressive failure and load transfer between the rows.

Technology of shield tunneling has been widely used in modern city subway system building, however, due to the limit of urban construction land resources, it is inevitable for the new building structures conflicted with existing one. Thus, it is essential to taking correct measures to guarantee the safety of existing structure. In this case, a typical case of metro shield tunnel crossing through city overpass bridge piles underpinning construction project is studied by the numerical method and site field monitoring. According to the existing overpass bridge structure, geological conditions and site operation environment, a suitable construction method of piles foundation underpinning plan for this project is adopted. In order to ensure the structure safety of the existed overpass bridge during the pile foundation underpinning construction, a numerical simulation model is established which takes the whole foundation underpinning structure and construction steps into consideration. The numerical simulation result shows that the stress and the settlement of the piles foundation underpinning structure is reasonable. After the comparing of the site monitoring data with the numerical model simulation results, it is found that the site settlement and stress results are highly consistent with the calculated results, and it proves the feasibility of the piles foundation underpinning construction scheme. Eventually, the site gauging settlement data of the overpass pier and the pile cap indicate that the original overpass structure is barely affected by the shield tunnel construction, the construction method can provide reference and experience for the future similar projects.

When exposed to sunlight, crystalline silicon solar cells (CSSC) will not only generate electric energy but are also heated by solar radiation. Such a self-heating effect makes the working temperature of CSSC 20–40 °C higher than that of the ambient temperature, which degrades their efficiency and reliability. The elevated operating temperatures of CSSC are mainly derived from absorbing photons that cannot be converted to electrons. Therefore, it is important to prevent CSSC from absorbing useless solar light to have a better cooling effect. In this paper, photonic structures based spectrum-selective mirror is designed to cool the operating temperatures of CSSC passively. The mirror could make CSSC absorb about 93% of the sunlight in the wavelength range of 0.3 to 1.1 µm and only absorb about 4% of the sunlight in the wavelength range of 1.1 to 2.5 µm. Meanwhile, the design has good compatibility with the radiative cooling strategy. By applying selective-absorptive and radiative cooling strategies, the operating temperature of CSSC could be decreased about 23.2 K and 68.1 K under different meteorological conditions. Moreover, unlike the single radiative cooling strategy, the spectrum-selective mirror also has effective cooling effects in high wind speed meteorological conditions.